20201201 13220700 TRUE CreateFeatureclass K:\snrc\research\slthrasher\Leiberg_Final\Leiberg.mdb\Spp_Ranges Wstn_Juniper # WestJuniper_Layer SAME_AS_TEMPLATE SAME_AS_TEMPLATE "GEOGCS['GCS_Clarke_1866',DATUM['D_Clarke_1866',SPHEROID['Clarke_1866',6378206.4,294.9786982]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]];-128.783917 31.111515 127999999.880791;0.000000 100000.000000;0.000000 100000.000000" # 0 0 0 K:\snrc\research\slthrasher\Leiberg_Final\Leiberg.mdb\Spp_Ranges\Wstn_Juniper Append WestJuniper_Layer K:\snrc\research\slthrasher\Leiberg_Final\Leiberg.mdb\Spp_Ranges\Wstn_Juniper TEST K:\snrc\research\slthrasher\Leiberg_Final\Leiberg.mdb\Spp_Ranges\Wstn_Juniper FeatureClassToFeatureClass C:\Projects\Sarah\Leiberg\SpecsShp\WestJuniper.shp K:\snrc\research\slthrasher\Leiberg_Final\Leiberg.mdb\Spp_Ranges Wstn_Juniper # "Shape_Leng Shape_Leng VISIBLE;Shape_Area Shape_Area VISIBLE;Species Species VISIBLE" SAME_AS_TEMPLATE SAME_AS_TEMPLATE # 0 K:\snrc\research\slthrasher\Leiberg_Final\Leiberg.mdb\Spp_Ranges\Wstn_Juniper file://\\LAPTOP-9OCJPADC\C$\Users\SG\Documents\ArcGIS\Projects\Yolo CWPP\01-Spatial Data\Leiberg\Leiberg.gdb Local Area Network 1.0 150000000 5000 In 1902, the U.S. Geological Survey published Forest Conditions in the Northern Sierra Nevada, California, by John B. Leiberg. <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN STYLE="font-weight:bold;"><SPAN>Title:</SPAN></SPAN><SPAN><SPAN> </SPAN></SPAN></P><P><SPAN><SPAN>Forest Conditions in the Northern Sierra Nevada, California – Digital Version</SPAN></SPAN></P><P><SPAN STYLE="font-weight:bold;">Date started:</SPAN><SPAN><SPAN> </SPAN></SPAN></P><P><SPAN><SPAN>September 12, 2005</SPAN></SPAN></P><P><SPAN STYLE="font-weight:bold;">Date completed:</SPAN><SPAN><SPAN> </SPAN></SPAN></P><P><SPAN><SPAN>January 10, 2005</SPAN></SPAN></P><P STYLE="font-weight:bold;"><SPAN>Summary:</SPAN></P><P><SPAN><SPAN>In 1902, the U.S. Geological Survey published </SPAN></SPAN><SPAN STYLE="font-style:italic;"><SPAN>Forest Conditions in the Northern Sierra Nevada, California</SPAN></SPAN><SPAN><SPAN>, by John B. Leiberg. This book contains generalized vegetation information on about 3.5 million acres between 39º and 40º N latitude and between 120º and 121.5º west longitude. This information is in the form of both a written description and maps of the area.</SPAN></SPAN></P><P><SPAN>In an effort to utilize the maps in this book in a GIS, we digitized the maps using ArcMap 8.3. First, all maps were scanned to a digital format (tif format). The digital maps were then georeferenced using ArcMap 8.3. Finally, we used on-screen digitizing techniques to delineate the polygons for each map unit of interest.</SPAN></P><P><SPAN>There are four main themes in the Leiberg maps and in the final digital product.</SPAN></P><OL STYLE="margin:0 0 0 0;padding:0 0 0 0;"><LI><P><SPAN STYLE="text-decoration:underline;"><SPAN>Cover</SPAN></SPAN><SPAN><SPAN> – The “cover” theme is divided into six distinct 30-minute quad maps (Bidwell, Colfax, Downieville, Sierraville, Smartsville and Truckee). In the “cover” theme, each polygon is labeled as either:</SPAN></SPAN></P><OL STYLE="margin:0 0 0 0;padding:0 0 0 0;"><LI><P><SPAN><SPAN>less than 2000 merchantable board feet/acre</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>2000-5000 merchantable board feet/acre</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>5000-10,000 merchantable board feet/acre</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>10,000-25,000 merchantable board feet/acre</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>greater than 25,000 merchantable board feet/acre</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>chaparral</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>cultivable</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>cultivated</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>pasture</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>rock</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>water</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>woodland</SPAN></SPAN></P><P><SPAN><SPAN>**** It is not clear whether the board/feet estimates in the maps are calculated using the “Michigan practice” or the “local practice”. The Michigan practice includes trees greater than 8” dbh and having at least 10 feet clear lumber in the trunk. The local practice includes pine trees over 12” dbh and fir trees over 16” dbh. Neither practice, we believe, includes incense cedar.</SPAN></SPAN></P><P /></LI></OL></LI><LI><P><SPAN STYLE="text-decoration:underline;"><SPAN>Culled Timber</SPAN></SPAN><SPAN><SPAN> – Polygons in this theme represent areas where cutting of trees has occurred, whether for timber, mining or fuel. No information exists as to the intensity the cutting. However, the intensity of cutting appears to vary from very light to complete clearing. The “culled timber” theme is divided into six distinct 30-minute quad maps (Bidwell, Colfax, Downieville, Sierraville, Smartsville and Truckee).</SPAN></SPAN></P><P /></LI><LI><P><SPAN STYLE="text-decoration:underline;"><SPAN>Species Distributions</SPAN></SPAN><SPAN><SPAN> – This theme shows the geographic distributions of:</SPAN></SPAN></P><OL STYLE="margin:0 0 0 0;padding:0 0 0 0;"><LI><P><SPAN><SPAN>Douglas fir</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>Grey pine</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>Mountain hemlock</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>Red fir</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>Sugar pine</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>Western juniper</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>Western white pine</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>Yellow pine (ponderosa and Jeffrey)</SPAN></SPAN></P><P /></LI></OL></LI><LI><P><SPAN STYLE="text-decoration:underline;"><SPAN>Fire</SPAN></SPAN><SPAN><SPAN> – These polygons represent fire perimeters and the intensity of those fires. The categories are as follow:</SPAN></SPAN></P><OL STYLE="margin:0 0 0 0;padding:0 0 0 0;"><LI><P><SPAN><SPAN>5-25% of timber burned</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>25-50% of timber burned</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>50-75% of timber burned</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>75-100% of timber burned</SPAN></SPAN></P></LI></OL></LI></OL><P><SPAN STYLE="font-weight:bold;">Data format and delivery:</SPAN></P><P><SPAN><SPAN>All data is delivered in a zip file named “leiberg.zip”. This zip file contains the following files and documents:</SPAN></SPAN></P><OL STYLE="margin:0 0 0 0;padding:0 0 0 0;"><LI><P><SPAN><SPAN>This brief final report (Leiberg_final_report.doc)</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>A geodatabase containing vector information for the four themes described above (Leiberg.mdb).</SPAN></SPAN></P></LI><LI><P><SPAN><SPAN>A folder labeled “images_rectified”, which contains the digitally-scanned, georeferenced images from which the geodatabase was digitized. </SPAN></SPAN></P></LI><LI><P><SPAN>FGDC metadata (leiberg_metadata.html). </SPAN></P></LI></OL><P><SPAN /></P></DIV></DIV></DIV> Authors: Sean A. Parks and Sarah L. Thrasher USDA Forest Service, Pacific Southwest Research Station, Sierra Nevada Research Center 2121 Second St., Suite A-101, Davis, California 95616 530-759-1717 (ph), 530-747-0241 (fx); sean_parks@fs.fed.us Source: Leiberg, John B. 1902. Forest Conditions in the Northern Sierra Nevada, California. United States Geological Survey, Department of the Interior. Government Printing Office, Washington D.C. 1902 Western Juniper Sierra Nevada TNF 20201201 /9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCADIASwDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD2O7z9 nQ4wVPNNtOF3nkE4FTTkLG6k9u9QQsUscgcjNYdQHzHhePvt0p0wEcROKiLGedPRRu4p92MwqPUj igREgJTIGRTTJzgDp1q0WSGMDPXgVCsQdyM+5FRyisQhwCc+nQ1HOyqOcYxke1WLqAkbkHK4NZGp SSPGiKPvnaDSkmh2Ktgqm5lZid/VautHLMpG/cMVEii1VI49pb+Ikc1cicISpxk8VPkBSg86E7HH HvV9zFIoWRce9SGNZE2HH+FVJpWiKxuPmzgUCJBAsbb0bIz0qVVLgjp6Utqh8shvWnsHAIQfnQAi MQduMnv70rRMj5Q5Bp1vs3ZkbDelX0MYAQ4J9a0UbodjP8vG3I98imXG4jaAfm9KuPHswe1QSYHz 9aloR59c3N5b3T7JmBVsU+LWL0n/AF7VPr1u0GoyuV+RzkHFZKjbk158nJSauQ2aZ1a8IOZ2qsdU vc/69qgGCMdKBH2xU88u4rmgNZv9v+vanf2vfcf6Q2azwCDx0pckdRVc0+4XLjahcnkyEk0p1C42 7fMIFVNwNDdKOeXcCz/aV4nyrMwU9aQ6ve78+e3NVUOQVJqJxh6XPLuO5pLrF7n/AF7U2bU7x0x5 7cc1RUgmpD6HpRzy7hcsRa3eqR+/YYq/Hr2oFci4fFYMyYKlRx3qWCULnPSqVSXcd2bcWpXklwg8 9vmODXcJA7MjtzgDFedWbq1zHg/xCvTVlCRoCOMDmu7DNtO5cWPCg9RTGk2yhcjB7VKhEgyDxVa7 QofMUcgV0lCsrKWZe9SF5PaoIbheAzcnpmrBh3HJY/hQBm3OZX8tRyWJzU0pENuFx2qKMFbyVjyE UYovGPkg/wATEDHtUCJLSLZCrEfMaeAXOWHABzUinCge1VJpWSchO9IRC+ZnRR0Vjz9KtwRqgJU5 PU5pkC5hbgb8k1VkkZGZScA96TdgJNTn2WpCNhjway/s5/dFtzsvIHYUkjtdXLSkHyYwCB60iXjs GVQNzH8qhyuAsMTPklcMe9WRE6dh06mliT90OMNUq7lxvXt1qRDo4/LBbcTuqrdR+a6SKDhT1q4o OzGc1FLhSuThQaufL9kmN+o5CwAIp4k3Zx260RSB13LyDTJNsT+YCAD1FQURSRja55zTYJGckux4 OOtPub6NBtXljVBZszvgfIefpQBqNNJIQq5ZPWpEVm4k+76iqFvcZ4AOegNTNLLGuOqnuapPuFy3 dWFvcRbJgGU+ormNS8PRhf8ARDhs8hq6S3uZD8jgEAZqWWOOaPCgButKVOM0FkcE2hXqnHl54zxV OWGa3O2RCp9678KVU7vve9R3UMM8RWWMMo9a53h10J5TgywxmjgitTVdIFtB50G4oT0x0rLiyRgj kVj70fdZDjqQniQAVIx+ba34U9kw3SpLS1e8uhBH98g4zUJNuyKKxGz5hSkb8Zq1Pp9zBL5EkLbz 0HrVRleJ9rKQcdxQ4tbgKqgHOak6io1yeAM0NlSPei9kKw5uFOagiBZc5qaXiI1JDEqxKOvvQkMl sI9tzH6k16Zbgm0Vt2cjvXnNsMTx/wC8K73TZNweFuQBxXfhdmaRL0MbxgktnmllVnwRzUikNCMH gioYGKuy5yvausooX1s5h8xch0OVx3pketRxRqk+RIByK2mRXTBrmNWgC3xwwHyjtSeg1qasZxgn ozE/Wm7BLfOcZC4zVgJhyRwijiqqswWQL96RvyFJiJ2OSzA8DpUEbL5XmsMsTnH1qZFKptY8elRI FWMhuVVsAVIh80qrGZApyB2rIkmNxLsXuetbkm1IQxAx3HtWMIyu5Y+5zUzESJCHIUHCr+tJ9mi8 5nI+mKjnk8pcKfnyMj0FWoo+A3esxDVYFge38qm3qVJGKoz7oGbZ0bpn1qRSiAIpJ45oAnY+WpfI HFRTBZYjFnkjOc1TvpTNOkaZwBUQSSSQ8nKjHBqrCuS210YgYW/h6H1qGWWW4wGJ21ILOUkgqQcc GligLKQ3yutS/IZZitI9uX7ikFqu07KSJHI+YkAcdatIhVRjNAGWC6kNnAUkAVoQyiVMtzntVe8j 5Uxrn1pit5aIw5yccUASRyPFd+U+dv8ADWj5X7ppB1xxVJ03OAeuMg06G642lqadtwJiPMCyEHcO CKo6hPJBHGyRlwzYIHYVp2+ZAfl4NSPaq7Be1U43V0BSWPz4NmBtbrkVDd6JbrYzSGJRIF+XAxWs IRGowMnPFOuW227BhyVp8it7wHmcTxvN+8YoucZxnFdJoWmJ9viuoZ0lC53AjpXLXDKHb610vg6J 5LmZuQm0fnXHQadRJoleR11xp9vdXEU8infH93BqOfR9PuiTLApbGM45q3HvHDYqXFei4rZlp3Ry 0ng63yPJmKgevNZWqeF5bOEziVXjXkjpXe1zXi262WiRK2C55HqKwq0qai3YGkcXIgZDikg4gQd8 U98BeaiVsKhIwOmK4EjMuWv/AB8R/wC9XcRbre8BYcSJgVw1qf8ASIz/ALddzOdzW6LywOfwxXZh tmaQNG3bNqjeq05VCfN60xMRokYzgUzUZjFbZX7x4rrKLRbIKjriqVxEgkw8YY46mrVuv7sMepFQ TKWkzmgELKcKIweo+Y0iwqPmFSsgz/M0ze2MYwBSaAgubVJwPM5CnI+tVoLKBLgkKd+455q8wYtz 35xSQqPOlc/ePFKzEyG83JbswPA54rM80IQzNyxrUmPmq8TAgNxmsqe2VVJLnIGRms5iZMIwfm65 GTUuNyDHHFZ9rdO0allJzWjH8w61mIpXbIcJkZB59qqyXWYAiZLMetJdIBd7QSwJ+bPrVuKywoJQ egoQDLeMAhpG68Vdj5BKJgetTQWUYBVh81TPEkYIXrVtN6sLWK4IAGaiOwzkJjPen3BEaqifeNRI gHTgjkmp0vqJk3k9S3T0qNpSXwfu4pzyYj7j+tNgiRY/MfqR37CnK1/dBXtqJMypbncPlNVkVWKN 0UH86SacT/IOfm4pVThVLHg8VIx8ko892wSAmAKqwq5uyW4XHyg1PnNxhjkMOBU0kZGWGOcD6UWu BLHMVjI469au205lBOBkVixSx/afsrZVhyCejVZCzW6lVOcHIqoysBsfcwTzWfq0zRQsy8/KTTRq ZEO1h8+OM96g1KcjSZJHUA44GauTvFsfQ4QoZJjhcknpXYeEFkQygghD0BFY+iafPdebNEMMOFz6 13Vham1tERsGTHzH1rmw1N35iYrqTEHdmpV6UgAxQDjiu9yuUlYU9K4jxhIDfom7ovT0rtZDhCSc ADNeYavO95fyuckhiB9BXLipWhYUtimX8wBfTrTztK7OpHNVV3JLjsanjGHOWzmuBMguWZzNEf8A arvbdcX+5u8YCiuBtOLmNenzV6LaW5EzTOc4UKo9q7sLsy4bE8aH+KmtbiZnZueMCpfvEY7U6U7I Gx1xxXUWMjYeRgHnpTBGcU2cFIFZM5x2Gap/bZ1ABLf9+TQBp43D3pnlkmnsCPmH405SCMigQx48 sDUUkRVyyfj71YNNIBAIoAzDueQgnB/lVKezcyHGXGcda0JVxdEHgGpSR5oAHA5NKeqREVuijFZM EGV+gAp7AxqQQA3YVoIQc+xqldMj3iAnAArJwKsYdqrSq7nmbPINacXnsoAGcdhUIti17JKmRH0H vWrBGkJ285xmpUdRBAWOQ33u/wBKp3lwwkKx9W4Bq9LiIM544zWaF3t5jjnsKqTtoMSNAG6lmPc1 IdqrtJ7UF/KQuV6nimqnmPukGAO1ZiGbhKRjOwdTTJH85ypOI19O9PuAFQqpI3dAO9CoQQu3avr6 0AI4iht8sAM8cCqaMzxO/ZelTagV8lhyfLwahjk8u0yx+8OB60AOXBmR/UVeh3OWHB4rPt1KoGx8 +MAGrturRLz35NCAa1ukkyKwHyNuDZ5q67gPtwOlVJWEbM7NwegpQRcANvA7U0AxwkjcgYJ/Ks7X TImmNGSSAd2fatYBEO3bhTyDTLuFbm2dc5BHSlJXTQEXhIxtp4Kt8wPNdI7BVJ7AZrivCN0sF1PZ OCp6qD612ZUOpU9CMGrou8ENbHJ6h4va3uGSKEMoOMk96oP4xvVn8zyl2EY25rN1uCFL+VIWYjJz n1q9ommw3lrK0657LXK6lWU+VMm7udLZ67Df6VLIxCyBCCuenFcJLOPNb5c5J5qVZn0y/kWBuFJH PcVBLP8AaJmcoqk9hU1armlfdCbuRAqZctx7U4KVcnsTxUbpk59KEkLfe5ANYXEaFt/x8x+zCvR7 aZmiw390V5nZuTdxe7CvQNzpECOwruws7JjRpQNvXPpwaecOcelZlneeYrMG69RVyOZc5rrUkzUs 44AFVJ7tYpShxxU7P8mRjNQtGjnJ60wLTdKQjPI4NK3SloENVjgqR061G8oAIGeMGnPIAcgZPeoZ AzuChB4PFAFe6ZNiliA2cio2l4I3gUSLLJhGtycdDjNV1ilJIZG+hWqVrWZm7810WY5HMTGPPPFP js08ol+WY5JNQQzlGKbCpAyRinzXJePapx64qZaLQE+5IHWEFWUHHHFSq26UtwOKzJvPBDIuQOxP WpEtriRS0jMAew4rJO7LEu73zZ/KTlQMMR3p0Zy3TgVbgtIVQbVGe5qhc3MULkBvm6YFTJPdiYt0 QVQZ6tRNMFwB8x9BVGe5LiIqDweCatQmKIbiwLdSagCRI3L+bKBwMKBTZyxids4xmh7rcUVFJ5qr Iud3nSFRtxtFMCJCZbBt3LOTTY0xCGcE7eBmrCouxRCD93AJpJJJoVAIGPcUhjFSQn5Bk5wTjpUr STKOV79ueKkVjJnGFAPamrb/ACku7AEk/SgRXvPNuVGEIweMVNCpt4EDBTIeoHOKoLqFmkpQ3Y4P 96pHvbKV9q3CAjkndS513C5qIxZdpXPrThGcEA49DUSTRmFZg6lQME5qwjgqGXG2qQHO6rZ3Fpcp qVsQXU/Mvc1v6Xr0F9CNx8uYfeVjimzRq6lmPvWWmlW9xOxcMhI6qcVK5oO8Q2KHiW2ji1AypgpI MjHrVTSdVNhPtfJhbgj0raTQoTuWeSVhnC5YmrI0K1a1MG35eocdaydOTlzLQVnuclqJjk1GWSI5 VmyKqE/vBmtjVtIOnbXRi0Z4yR0rEkB35Fc001LUknI/KoEAErKOlTjoDUIUiVm7YqRFu0H+lRf7 wr0RWBjyewFebWbF7uM/7VehQxuyKM8Yrsw2zLiV4l2Xkrpwrdqtxvge1OFqoUgHLZpwgUY3np0F dSTLsWFOU4PXoamRRtGTWZeTTpGq2cQkkHVWOOKal1qBQE2iA+zn/CtBm05wppkLs65PNOcEoagR JVHoBWkUmmZybTRI6HBwMU2NMKpJ5IqUkkYpQAAAe1RYsWM5B4pvlqASRyetP4pOpwfSgCu6Bxhc Aj+VRSW0fmBh97uKmRSJW9KUqFLMeamwFdEG5gw5p7sVQ4GaEGV3P1Jzim4Zk3McZHAqWJlaGXnl sc9KqRIs1zJKVG0nCg1K0LA5UZGcn6U4KF5UHpUqLcSW7DPssIyNvWiOzEILBs5HA9Kcm7K57dSa V5yxKxjJ9am1hoi2bk3byDTZokNsy479alUY5YUyYgKAec9qQCR4SFVx93vQ0qyZRlGD3qBpC2QS AMcVG0mPuZ+tIC3GqK7Y5GapXzy3oMMDbFztJ9fWnoksgWNcqD1buavRWscSfTqTRuBmjS7KKJY3 jXd3PPNOGlWMsZ2QKCRweat71Mb7mAQfxNWbP4gt4BsjPmsDzjgVL5UtRaHO3cE1pO8TFwuTjnrU ttrF3acK5ZR/CakvtXhvZFWW3woBwQeQazDhgdp4rkk0neLINyPXr65YpFEpJ7Cmx6xfQzqnkh3z jac1Y8KwAmWd8cfKKd4hukRyI22yHuPStve5OZsroLc3Or+QZXiWIA5wOTUVvrepopDQb1Hcil8P 3c0m8zSMwzhQea6gBTFncMntVxTkuZMZyV54he5iaBrdADnOc5rBbvxWvr8UC6oxjUhiOT61lfWu eo25WbJY5WyuCKQqNp9xQeBSsQFqHboSr9RunttuE/369GZ1REIJ6CvN7VSL6H0LAmvRUQSRLg9B XVh3aLNEO85QQd/NWodjIWU7qyYwy3D56jpUlvKVdsHA6mulTKRrjHXFAUbRxUUUhZOufep1YY5B zWiZRZPSg8rQelNckDiqEInLc9cU/HzZqlbtc/asOo8vHXvV6gEB6UzknNPPNLjPFMCtLuRcjpQe EDe1SuN6lfwqJ1wgXPHSpaAjnOItw+8OlOALqoNHlliQelSkAAGkBnylopDg8EdKjV8x7u5q3dx5 UEetZlpHNPuAPyg45pKTjexEo3J1kj8wo7DcB0pskixfdXJParX9mxEbmJ345PrSDT13KxJapcWO xmu1zIc7AB6U1UuJJQGwOODW1Lbh1+UYxVCOKRpyQ2FXj61Di0BWWxAc7yW96JLZYMMCRnjGauzT rEMZz7VmzzefMgB6cn2pOwE9rLvbceF7U++kxEoH8RxVRZRFhEGWHT2pVkN1OgYAKn6mkBDrqyDS dsSE5xux2FcaFIBI616POF8hvM6ba4uLSrm/lklhGI88Z71hWg200S0U4UglnVXOwbf1ppiwHcMN qnGPWrF7pdzYIskq9e9UoiWGTnrXO9NGhGlo9ybW/TLkKxwRnirGvwrHfrIxyGXkCsn7vI60M7SH 5iSfc1Sn7vKFyzFqMkSeXawhT69TWnZ61LbQnfbOf9tiaxYtQnt4fLQqAD1xWtZyNPamS7vgkbHG 3aM/yrSEr7MaIdT1WHUIR+62zKeo71mEZ57U+5WOOd/JJaMH5Se9MUkjpWMm29RMXtQy5UikkBGM daU8cdaVhBZAtcRr/tAZr0aBFWMEddtec2gxdp2ywxXotu37gHOeOtdWH2ZaIJHjjLK5Ab1qA/Ll k6YqCfd5zcdW61NCPPk2gnjknsK3KNS3AVB9Kmyp5zUW5UiOO1QefIwyinFapjubR6Un8NLVea5W Dgq7f7q5rQCUEZXHen1RS8R5UjEcoJPUrxV6gAoopCdpAoAQDGT61BMGCseoyCKnfBHPQVFNIBES OuO9PYGrqwg4Ib1FMuJNoXHeo5JCscec5PWmTuWjCqMkcVL1DYgu3up1GwAJ39auW8AtoVUd+tRC bYg3qcDjIFIs0kmJVX930pAWpJEiBdjVZr0qCfKbnpStamWQmQkr1GDVhVCqFzwKAKizzNGdq4Zu 5qo4uWZyCAT29K1GAx04qs28Auqj3NRIRQazkUYLMcYyc1Gls0ZcAHAPWtBJTIpywBoaNlGC/Wpa XQRTSBXjPJ3iontRt3oSrj2qwu2Ms4J+ZsirGSF3OnTsfSjlT2Ay5Hurqz8qHId/lLenvVGK0vtL yY5jJt5KHuK6FCCNqKF9cVT1GZISDtdpAOMdPxqXGIjntc1aO/so0Tcsu75lPasRTgcmrV5E00rT IMhyc4GMVag09ItNe8njJwcKucVxzUpS1JKltZS3h/dAYzyzHAFXpNBuFUmJ45eMnaRWZ57xghWZ VY9Aakgvri1k3xyEYqYuHVBoV5UMZIdcMOoNOjtp5kzHGzDOOBUlzePeTCSZVBPUqMZrq7M2yWa+ TIoQDLEGqpwjJvXQLXOTe0uY1+eJxjvioMy5wFzzXRxX323VVh3Zt0y31xWbdRvd6hJ9miJGeiil KEVrECkASMtwaWppYJYTiWNl7ciocc81mxCRJm7iYf3gDXcwSMoCk444riITi4QcAZrtUnjMIAU5 211YdaMuJHOs1wwCDbz19qtReTZqV37nxzjtUkIMNvuUfvAvfsKyIlEkzO7E7yQAOldGxRu2Uq3B KDuO4rSKEcKQAPaqWmWEdu3mgsWIxycitPbnqa3SVtBiKcimMoBJx1pVGD9ac3SmBGqgFeKlqIck EdM1JzQCFprruU84pck005PGeKAAEMh+lMbbxux6c0/ZjoaqfY2+0GRnyP7tMAuQHKgYz2p4TaOf QYoFuAwY5JzT2Qhsnik9gt1HYTbjbn1FNUAcBSB6U4HgYFGTSAQ8EntTVKt8xNEy7kIHANVUsI0B bfLyMY3UgLEu1hjdx7VWuN+DGp+U0Q2KQzF/Mc+xNTKgLMz/AHc8UmhFQYQn0AqNN0qmeUnaOFA7 1JPCZrjbHwtWvIiiUK5yRUKAWK8CkHdIAP7o9KZcy4h38YLY+tQ39yoO1WG49ge1UHuHYgtllB+V P603tZBsXoZW2Nx1PWnHavzdc9c1VW8CJgjn0FRSTXUpIQBEx1PJqGmtybiCRI3MgVSjHB46Vna1 diWzKqQuW+VfbvVoWUnkNlyw5Jz0qA2yXUeJEJKjA+lRJOUdBsw7W0+1soLYA9OtdFDo9pmM7NwH UnuaWz0xICrxr8h4BPatPqBGgB7VEKUUhJFDWNKinhDxKqMg7d65NruVIzCpwnt3rrtfke30pvLf kkA+1cQD8pzWVeyegmaehOTqYyBjac/lVux1FbO6nVlAVmb5u4OayLCV4r2JkP8AEBW5ryWsESiF E8yT5mI7VMG1C66B0F0rUo3dobob1yTvI6Cq2oTWU88xiDsx+6VHArLjlcRsigfMeT3rsNC0uCOz SdkzI4zzW2HhKu+RESnyq5ykUJMyKc8nvXfWlmkaISRkCo7nTbeco2wKyNnIq4BgAV6FHA8l02Z+ 2a2Kl/IYYZPU8fnVdYlie1A64H61JqLDJXknbVUuVMDE/KoGfauafuyaOhO5vKcd6fvI/iqhZ3Ab eWbjtVkhz91QR6mtFrsVY0u4pGYAUgUkk7jUboV53GtGUhfNjBwWAPpS+dG77VYE+gNUpLGKY5kD MfY4qSG0t4ZEeNTuUYHJpiLuPWo3uI046n2qQ5K8daoywMgLEikxpFqKbzcnGKlP61mK5Q5BqxHc HdhufShMLEwbAYY6UhzIMelSHBP15po+UnFABjoOfXNI2etG8AjNBPG6kxDS26mn/WdeMUkZ+Vyf U00MGbJ6UgHOpwKZNJwqJyR1NP3mRSv61TuphFCMMMk9PajSwtbkmSj72OF6Z9KzL6981vKh3bN3 zPntU0szXTCFD8gGSRVmWJI7UKEABP41LegGQbQsokTkn19KW0VMneDnvmtVUAHAFQyJHCdwHOCc Vm22TZERtIBjAPJzSqE+6gyfWo5p/LXex+Y8ACmwu3yxhSvHX1qRlh1QKd2OeKptCInSRM5UHAzV uVFCjJyc9KhIM0nBwi07gPRyIdvRR3NPs48guaiYM7+Wi8DmpZ5xZ25ZiAqjk+tFmtRXMLWbxob1 7aXaYpBgEjpXNyxOqglcK33T61qXMdxrFybgqREDx9KoXs6y3CpED5cYwK46jvq/kJlWP5JAQejC tzVY47qGOeJ4wyoAyg4NUrS7t7eJt9uskucjdWk12l/aRxrbLG8jhcgU4RTTV9wJ9J8OxTWkdxM5 y/OBXTQQpbwrEn3VGBSW8SwW8cS9FGKlr36FCFKKstTjlJtiN0paQ9KCQFya2vbUXQrXcYLqxHbB rPnYLmNMbjwQfSr91IpQdemazpi7yqFUjd3rx52lNs7oqyLFkNuVIyB1PatNLgbBgMfcLmqKxGGF lHfua0bUf6OvGaqBaNFfuimuuaSOVWQHI/Ont0rUERhNr0jEJLkDg9akH3z9KCo3g02CHdaiuBmI 0rsIVLH7o5NNguIrpCYzkA4pAUgjHopqaGBywJGBmrmAO1DE7SB1oSHcaM9D1FJkHPqKijc+YfMO D6VISDz2qpRtoTGXMhRGA26hwClKG+XJ4qKV94KoeakYjZ27U703aIx7U22imR2MpBBPGKkc7n2f nUgRKpWAqerGs8eTHdusy7nA4+lajAFxjoBWVdMovY5MZkAwR6ihgXIhFE4+ULkdKilmR7gc/LtP fvSeS8hEj8bj+QqytnBsyyjA5yakRBG2VyazJ5jJcuAcAcHPpWs1xGyYAAXsa564+aaVUHO4dKzk rCsT7vMvT5ah9oA5rUCAhdw+YVlR3AtjtEeWHJq/HdxkB2ZQT71IBeNsVVUYZzjPpUVu26Rioyic D3NQzzfaLrYhDKvORVhf9UscY2g/eNAEjSlE3bhXM69qgmDW6N8qnkirWt6h9mT7JBzNJxu9KzF8 Pag0YYxqcju3NZ1akpe6tSXpois2qTtarCjBUHUjqapbzyR+NElrLBK8bAgg8ikTrg9a45NvcRPZ PDHcF7hd6gfKPetOG9uLi7tmIjSMSAIuOKzUtnmOEUtj0FWYdJv5mXAKBTkZOK0pyktkCO+jz5a7 uuKdWPo090JprO4beI1yG71sV9FQq+0hzWOWpHlYh6UFQy4NDdKO1aPrcldCIgMShGVHSs9Jgmpl MZBGK08ZBBNc9dOILzzIyTz+deO2egje8nD72OcnpV9A235cAVQizNArNkZHStWEYiXjtWsARWt7 GLYrbWUg5AJNXSciiirGNbPDCnH7woop9A6gyh1KsMg1GsSQg+WAvqKKKAY7du4FPHFFFIBrIu7J FRMhQ/L+VFFO4EUkblxvY7KlMargg89qKKlgIxIIH8VKo+UsTz3oooFYqzzeTgsPvcVXs7d2nMrK MEcZ7UUUhmg+1EJ7Csa61MyRGNOATgmiiplohbFCSZ2UqW2jOeKaEUx7/NCgn8c0UViJFm2t1Dbi wcNT3soVO7fgdhRRTAI4OMINqE8nuauqiqm7HAoopAZNvp0U98944LHPyg9q1ixTAxmiihJIRWaz t7ibzHjXzPWsTWfD7mXzrSPIPVRRRWkqUZUrshv3rGaukahgbYnGfQ4qVLHWIGyiyBu+eaKK5VSS 2KsadlJdQ30TNEQzrskX9c10gORmiivUwTdmjCutmI3SlHNFFdctmZR6CPjaa5pVzqAV+FMnf60U V47O5HUoAFxjpV6L/VL9KKK2iNH/2Q==